Relative Pose from SIFT Features
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00362923" target="_blank" >RIV/68407700:21230/22:00362923 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-19824-3_27" target="_blank" >https://doi.org/10.1007/978-3-031-19824-3_27</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-19824-3_27" target="_blank" >10.1007/978-3-031-19824-3_27</a>
Alternative languages
Result language
angličtina
Original language name
Relative Pose from SIFT Features
Original language description
This paper derives the geometric relationship of epipolar geometry and orientation- and scale-covariant, e.g., SIFT, features. We derive a new linear constraint relating the unknown elements of the fundamental matrix and the orientation and scale. This equation can be used together with the well-known epipolar constraint to, e.g., estimate the fundamental matrix from four SIFT correspondences, essential matrix from three, and to solve the semi-calibrated case from three correspondences. Requiring fewer correspondences than the well-known point-based approaches (e.g., 5PT, 6PT and 7PT solvers) for epipolar geometry estimation makes RANSAC-like randomized robust estimation significantly faster. The proposed constraint is tested on a number of problems in a synthetic environment and on publicly available real-world datasets on more than 800 00 image pairs. It is superior to the state-of-the-art in terms of processing time while often leading more accurate results. The solvers are included in GC-RANSAC at https://github.com/danini/graph-cut-ransac.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Computer Vision – ECCV 2022, Part XXXII
ISBN
978-3-031-19823-6
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
16
Pages from-to
454-469
Publisher name
Springer
Place of publication
Cham
Event location
Tel Aviv
Event date
Oct 23, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000903565400027